{ "cells": [ { "cell_type": "markdown", "id": "efe9d40f", "metadata": {}, "source": [ "# Tutorial 0 - SARA-mini\n", "\n", "This tutorial introduces the basic classes and methods of the SARAwater package.\n", "\n", "The figure below illustrates the workflow of the sarawater package, highlighting its components. In this tutorial, we will focus on the incoming flow time series ($Q_{nat}$), the flow requirement ($Q_{req}$), and the released flow time series ($Q_{rel}$). These three quantities contribute to the mass balance at the diversion, which reads\n", "\n", "\\begin{equation*}\n", "Q_{nat} = Q_{abs} + Q_{rel}\n", "\\tag{1}\n", "\\end{equation*}\n", "\n", "\n" ] }, { "cell_type": "markdown", "id": "4d1f31ea", "metadata": {}, "source": [ "## Importing external libraries\n", "\n", "Let's start by importing the necessary external libraries." ] }, { "cell_type": "code", "execution_count": 2, "id": "d46cb89f", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "from numpy import ndarray" ] }, { "cell_type": "markdown", "id": "1c07fb8a", "metadata": {}, "source": [ "## Defining SARA classes\n", "\n", "The classes defined below are a shrinked version of those implemented in the package. However, they are sufficient to get the basics off how SARA works!" ] }, { "cell_type": "markdown", "id": "1bbec8e7", "metadata": {}, "source": [ "### The `Scenario` class and its child classes" ] }, { "cell_type": "markdown", "id": "5e172df2", "metadata": {}, "source": [ "The parent class `Scenario` and its child classes `ConstScenario` and `PropScenario` are used to define different water management scenarios for a river reach. Each scenario specifies how much water is required to be released from the reach (i.e., the \"flow requirement\") based on different criteria." ] }, { "cell_type": "code", "execution_count": null, "id": "a8aa56a1", "metadata": {}, "outputs": [], "source": [ "class Scenario:\n", " def __init__(self, name: str, description: str, reach, Qabs_max=None):\n", " \"\"\"Parent class for all types of scenarios. Contains the name and description of the scenario.\n", "\n", " Parameters\n", " ----------\n", " name : str\n", " Name of the scenario.\n", " description : str\n", " Description of the scenario.\n", " reach : Reach\n", " The reach object associated with this scenario.\n", " Qabs_max : float, optional\n", " Maximum value for the water abstraction, by default None (which takes the value from the reach object).\n", " \"\"\"\n", " self.name = name\n", " self.description = description\n", " self.reach = reach\n", " self.Qreq = None # Flow requirement time series\n", " self.Qrel = None # Released flow rate time series\n", " if Qabs_max is None: # Maximum abstraction\n", " self.Qabs_max = reach.Qabs_max\n", " else:\n", " self.Qabs_max = Qabs_max\n", "\n", " @property\n", " def Qnat(self) -> ndarray:\n", " \"\"\"Get the natural flow rate time series from the associated Reach.\"\"\"\n", " return self.reach.Qnat\n", "\n", " @property\n", " def dates(self) -> list:\n", " \"\"\"Get the dates from the associated Reach.\"\"\"\n", " return self.reach.dates\n", "\n", " def compute_Qrel(self) -> ndarray:\n", " \"\"\"Compute the released flow rate time series for the scenario.\n", "\n", " Returns\n", " -------\n", " ndarray\n", " Released flow rate time series.\n", " \"\"\"\n", " if self.Qreq is None:\n", " raise ValueError(\"Qreq must be set before computing Qrel.\")\n", "\n", " Qrel = np.zeros_like(self.Qnat)\n", " case1 = self.Qnat <= self.Qreq\n", " case2 = (self.Qnat > self.Qreq) & (self.Qnat < self.Qabs_max + self.Qreq)\n", " case3 = self.Qnat >= self.Qabs_max + self.Qreq\n", " Qrel[case1] = self.Qnat[case1]\n", " Qrel[case2] = self.Qreq[case2]\n", " Qrel[case3] = self.Qnat[case3] - self.Qabs_max\n", " self.Qrel = Qrel\n", " return Qrel" ] }, { "cell_type": "markdown", "id": "beb05704", "metadata": {}, "source": [ "`ConstScenario`: the child class for scenarios with fixed monthly flow requirements" ] }, { "cell_type": "code", "execution_count": 4, "id": "b03b2c3f", "metadata": {}, "outputs": [], "source": [ "class ConstScenario(Scenario):\n", " def __init__(\n", " self, name: str, description: str, reach, Qreq_months: list[float], **kwargs\n", " ):\n", " \"\"\"Constant flow rate scenario.\n", "\n", " Parameters\n", " ----------\n", " name : str\n", " Name of the scenario.\n", " description : str\n", " Description of the scenario.\n", " reach : Reach\n", " The reach object associated with this scenario.\n", " Qreq_months : list[float]\n", " Monthly constant flow rates.\n", " \"\"\"\n", " super().__init__(name, description, reach, **kwargs)\n", "\n", " if len(Qreq_months) != 12:\n", " raise ValueError(\"Qreq_months must have 12 elements.\")\n", " self.Qreq_months = Qreq_months\n", "\n", " # Map the monthly flow rates to the dates of the reach\n", " self.Qreq = np.zeros_like(self.Qnat)\n", " for i, month in enumerate(self.Qreq_months):\n", " month_mask = np.array([date.month == i + 1 for date in self.dates])\n", " self.Qreq[month_mask] = month" ] }, { "cell_type": "markdown", "id": "d4562966", "metadata": {}, "source": [ "`PropScenario`: the child class for scenarios with flow requirements proportional to the incoming flow. In scenarios with a proportional flow requirement, $Q_{req}$ is computed as a fraction of the incoming flow discharge, $Q_{in}$, according to the formula:\n", "\n", "\\begin{equation*}\n", "Q_{req} = Q_{base} + c_{in} \\cdot Q_{in} \\tag{2},\n", "\\end{equation*}\n", "\n", "where $Q_{base}$ is a base flow requirement (e.g., to maintain minimum ecological conditions), and $c_{in}$ is a coefficient that defines the proportion of the incoming flow to be included in the flow requirement.\n", "\n", "This formula is then adjusted to ensure that $Q_{req}$ remains within user-specified minimum and maximum bounds, $Q_{req,min}$ and $Q_{req,max}$, respectively. This step is needed because low flow requirements may cause severe alteration in the downstream reach, while high flow requirements may lead to a very low water abstraction, which might not be sufficient. The complete definition of $Q_{req}$ in proportional scenarios is given by the piecewise function:\n", "\n", "\\begin{equation*}\n", "Q_{req}=\n", "\\left\\{\n", "\\begin{array}{lll}\n", "Q_{req,min} & \\text{if} & Q_{base} + c_{in} \\cdot Q_{in} \\leq Q_{req,min}\\\\[1ex]\n", "Q_{base} + c_{in} \\cdot Q_{in} & \\text{if} & Q_{req,min} < Q_{base} + c_{in} \\cdot Q_{in} < Q_{req,max}\\\\[1ex]\n", "Q_{req,max} & \\text{if} & Q_{base} + c_{in} \\cdot Q_{in} > Q_{req,max}\\\\\n", "\\end{array}\n", "\\right.\n", "\\tag{3}\n", "\\end{equation*}" ] }, { "cell_type": "code", "execution_count": null, "id": "7e721f3a", "metadata": {}, "outputs": [], "source": [ "class PropScenario(Scenario):\n", " def __init__(\n", " self,\n", " name: str,\n", " description: str,\n", " reach,\n", " Qbase: float,\n", " c_in: float,\n", " Qreq_min: float,\n", " Qreq_max: float,\n", " **kwargs,\n", " ):\n", " \"\"\"Proportional flow rate scenario.\n", "\n", " Parameters\n", " ----------\n", " name : str\n", " Name of the scenario.\n", " description : str\n", " Description of the scenario.\n", " reach : Reach\n", " The reach object associated with this scenario.\n", " Qbase : float\n", " Base flow rate.\n", " c_in : float\n", " Coefficient for inflow.\n", " Qreq_min : float\n", " Minimum value for the prescribed minimum released flow rate.\n", " Qreq_max : float\n", " Maximum value for the prescribed minimum released flow rate.\n", " \"\"\"\n", " super().__init__(name, description, reach, **kwargs)\n", " self.Qbase = Qbase\n", " self.c_in = c_in\n", " self.Qreq_min = Qreq_min\n", " self.Qreq_max = Qreq_max\n", " self.Qreq = Qbase + c_in * self.Qnat\n", " self.Qreq[self.Qreq < Qreq_min] = Qreq_min\n", " self.Qreq[self.Qreq > Qreq_max] = Qreq_max" ] }, { "cell_type": "markdown", "id": "b711a833", "metadata": {}, "source": [ "### The `Reach` class" ] }, { "cell_type": "code", "execution_count": null, "id": "d4b2174f", "metadata": {}, "outputs": [], "source": [ "class Reach:\n", " def __init__(self, name: str, dates: list, Qnat: ndarray, Qabs_max: float):\n", " \"\"\"Represents a river reach.\n", "\n", " Parameters\n", " ----------\n", " name : str\n", " Name of the reach.\n", " dates : list[datetime]\n", " List of dates for the time series.\n", " Qnat : ndarray\n", " Natural flow rate time series.\n", " Qabs_max : float\n", " Maximum value for the water abstraction.\n", " \"\"\"\n", " self.name = name\n", " self.dates = dates\n", " self.Qnat = Qnat\n", " self.Qabs_max = Qabs_max\n", " self.scenarios: list[Scenario] = []\n", "\n", " def __str__(\n", " self,\n", " ): # This method defines what is returned when we print() a Reach object\n", " return f\"{self.name} is a Reach object with a flow time series with {len(self.Qnat)} elements. The date range starts from {min(self.dates)} and has {len(self.dates)} elements. The maximum flow abstraction is Qabs_max={self.Qabs_max} m3/s. So far, {len(self.scenarios)} scenarios have been added.\"\n", "\n", " def add_scenario(self, scenario: Scenario):\n", " \"\"\"Add a scenario to the reach.\n", "\n", " Parameters\n", " ----------\n", " scenario : Scenario\n", " The scenario to add.\n", "\n", " Returns\n", " -------\n", " Reach\n", " The current reach instance.\n", " \"\"\"\n", " self.scenarios.append(scenario)\n", " return self\n", "\n", " def print_scenarios(self):\n", " \"\"\"Print the list of scenarios added to the reach.\"\"\"\n", " for i, scenario in enumerate(self.scenarios):\n", " print(f\"scenarios[{i}]: {scenario.name} | {scenario.description}\")\n", " return None" ] }, { "cell_type": "markdown", "id": "c13def8e", "metadata": {}, "source": [ "## Let's create a Reach!" ] }, { "cell_type": "markdown", "id": "d9126f3e", "metadata": {}, "source": [ "First, let's specify the path to the input CSV file containing the flow discharge time series for the reach.\n", "\n", "**NOTE**: the CSV file should have at least two columns: \"Date\" and \"Q\", where \"Date\" contains the timestamps and \"Q\" contains the flow discharge values in cubic meters per second (m³/s)." ] }, { "cell_type": "code", "execution_count": 6, "id": "c508c5da", "metadata": {}, "outputs": [], "source": [ "csv_filepath = \"daily_discharge_30y.csv\" # The csv file must be in the same folder as this notebook" ] }, { "cell_type": "markdown", "id": "a1f4df8b", "metadata": {}, "source": [ "Then, let's extract the timestamps and discharge data from the CSV file. To create a `Reach` object, we need to convert the \"Date\" column to a list of datetime objects and the \"Q\" (flow discharge) column into a numpy array." ] }, { "cell_type": "code", "execution_count": null, "id": "dc62ec97", "metadata": {}, "outputs": [], "source": [ "# Read CSV with automatic date parsing\n", "input_df = pd.read_csv(csv_filepath, parse_dates=[\"Date\"])\n", "\n", "# Convert the \"Date\" column to a list of datetime objects\n", "datetime_list = input_df[\"Date\"].dt.to_pydatetime().tolist()\n", "\n", "# Convert the \"Q\" (flow discharge) column into a numpy array\n", "discharge_data = np.array(input_df[\"Q\"].to_list())" ] }, { "cell_type": "markdown", "id": "3953ed3b", "metadata": {}, "source": [ "### Initialize a reach object" ] }, { "cell_type": "markdown", "id": "57c8a19f", "metadata": {}, "source": [ "The only ingredient left to create a `Reach` is the maximum flow discharge that can be abstracted from the reach." ] }, { "cell_type": "code", "execution_count": 8, "id": "b795cce1", "metadata": {}, "outputs": [], "source": [ "Qabs_max = 3" ] }, { "cell_type": "markdown", "id": "3101f0d0", "metadata": {}, "source": [ "Finally, let's create our `Reach` object!" ] }, { "cell_type": "code", "execution_count": 9, "id": "e3b0187d", "metadata": {}, "outputs": [], "source": [ "my_reach = Reach(\"My Reach\", datetime_list, discharge_data, Qabs_max)" ] }, { "cell_type": "markdown", "id": "152330bd", "metadata": {}, "source": [ "## Adding scenarios to the reach object" ] }, { "cell_type": "markdown", "id": "93ddea8e", "metadata": {}, "source": [ "### Minimum Flow Requirement (MFR) scenario with fixed monthly requirements" ] }, { "cell_type": "code", "execution_count": null, "id": "00fd0fa3", "metadata": {}, "outputs": [], "source": [ "Qreq_months = np.array(\n", " [0.1, 0.1, 0.1, 0.12, 0.12, 0.12, 0.12, 0.1, 0.1, 0.12, 0.12, 0.1]\n", ") # values are in m3/s, representing minimum release for each month\n", "\n", "# Create a constant scenario with these values\n", "const_scenario = ConstScenario(\n", " name=\"Constant Scenario\",\n", " description=\"Minimum release scenario with constant monthly values\",\n", " reach=my_reach,\n", " Qreq_months=Qreq_months,\n", ")\n", "\n", "# Add the scenario to the reach\n", "my_reach.add_scenario(const_scenario)" ] }, { "cell_type": "markdown", "id": "a1fd16d7", "metadata": {}, "source": [ "### Proportional release scenario" ] }, { "cell_type": "code", "execution_count": null, "id": "d21108bc", "metadata": {}, "outputs": [], "source": [ "prop_scenario = PropScenario(\n", " name=\"Proportional Scenario\",\n", " description=\"Proportional scenario with arbitrary parameters\",\n", " reach=my_reach,\n", " Qbase=0.06,\n", " c_in=0.3,\n", " Qreq_min=np.min(Qreq_months),\n", " Qreq_max=1.3 * np.max(Qreq_months),\n", ")\n", "my_reach.add_scenario(prop_scenario)" ] }, { "cell_type": "markdown", "id": "af625209", "metadata": {}, "source": [ "### Let's check we added the scenarios correctly" ] }, { "cell_type": "code", "execution_count": 12, "id": "076813a7", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "scenarios[0]: Constant Scenario | Minimum release scenario with constant monthly values\n", "scenarios[1]: Proportional Scenario | Proportional scenario with arbitrary parameters\n" ] } ], "source": [ "my_reach.print_scenarios()" ] }, { "cell_type": "markdown", "id": "a63286af", "metadata": {}, "source": [ "## Compute the released flow discharge for each scenario\n", "\n", "Given the incoming flow discharge $Q_{nat}$, the flow requirement $Q_{req}$ and the maximum abstractable flow $Q_{max}$, the released flow discharge $Q_{rel}$ is computed as:\n", "\n", "\\begin{equation*}\n", "Q_{rel}=\n", "\\left\\{\n", "\\begin{array}{lll}\n", "Q_{nat} & \\text { if } & Q_{nat} \\leq Q_{req} & (4.1)\\\\[1ex]\n", "Q_{req} & \\text { if } & Q_{req} < Q_{nat} < Q_{req}+Q_{abs,max}& (4.2)\\\\[1ex]\n", "Q_{nat}-Q_{abs,max} & \\text { if } & Q_{nat} \\geq Q_{req}+ Q_{abs,max} & (4.3)\\\\[1ex]\n", "\\end{array}\n", "\\right.\n", "\\end{equation*}\n", "\n", "Where the three cases correspond to the following:\n", "* $(4.1)$ The incoming flow $Q_{nat}$ is lower than the flow requirement $Q_{req}$; therefore, no water is abstracted and the released flow discharge $Q_{rel}$ equals the incoming flow. This usually happens in low-flow periods.\n", "* $(4.2)$ There is enough incoming flow to satisfy the flow requirement, and the abstracted flow discharge $Q_{abs}$ is lower than the maximum abstractable flow $Q_{abs,max}$. Recall that, according to Equation $(1)$, $Q_{abs} = Q_{nat}-Q_{rel}$ (where, in this case, $Q_{rel}=Q_{req}$). This is the most \"common\" case, where the flow requirement rule is applied straightforwardly.\n", "* $(4.3)$ The incoming flow $Q_{nat}$ is so large that the maximum abstractable flow can be diverted while still releasing a flow rate larger than the flow requirement. This usually happens during flood events.\n", "\n", "The piecewise function $(4.1-4.3)$ is implemented in the `compute_Qrel` method of the class `Scenario`; therefore, to compute the released flow time series for each scenario we can simply write" ] }, { "cell_type": "code", "execution_count": 13, "id": "424b2ca5", "metadata": {}, "outputs": [], "source": [ "for scenario in my_reach.scenarios:\n", " scenario.compute_Qrel()" ] }, { "cell_type": "markdown", "id": "a85b2090", "metadata": {}, "source": [ "## Plot the released flow discharge time series for each scenario" ] }, { "cell_type": "code", "execution_count": 14, "id": "77e8c5e5", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(my_reach.dates, my_reach.Qnat, label=\"Natural Flow\")\n", "for scenario in my_reach.scenarios:\n", " plt.plot(scenario.dates, scenario.Qrel, label=scenario.name)\n", "plt.xticks(rotation=45)\n", "plt.legend()\n", "plt.ylim(0, 0.5)\n", "plt.tight_layout()" ] }, { "cell_type": "markdown", "id": "58572b07", "metadata": {}, "source": [ "What a messy plot! Lets focus on one year only. First, let's create a Boolean array (a `mask`) to filter the dates within the year 2018." ] }, { "cell_type": "code", "execution_count": 15, "id": "260f3d5a", "metadata": {}, "outputs": [], "source": [ "start_date = pd.to_datetime(\"2018-01-01\")\n", "end_date = pd.to_datetime(\"2018-12-31\")\n", "mask = [(dt >= start_date) and (dt <= end_date) for dt in my_reach.dates]" ] }, { "cell_type": "markdown", "id": "abf7bac6", "metadata": {}, "source": [ "Then, let's plot the released flow discharge for each scenario in the time interval we specified" ] }, { "cell_type": "code", "execution_count": 16, "id": "f1a0efda", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(np.array(my_reach.dates)[mask], my_reach.Qnat[mask], label=\"Natural Flow\")\n", "for scenario in my_reach.scenarios:\n", " plt.plot(np.array(scenario.dates)[mask], scenario.Qrel[mask], label=scenario.name)\n", "plt.xticks(rotation=45)\n", "plt.legend()\n", "plt.yscale(\"log\")\n", "plt.grid()\n", "plt.tight_layout()" ] } ], "metadata": { "kernelspec": { "display_name": "saraenv", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.12" } }, "nbformat": 4, "nbformat_minor": 5 }